Vectors, axes, and periodic phenomena have direction. Directional variation can be expressed as points on a unit circle and is the subject of circular statistics, a relatively new application of statistics. An overview of existing methods for the display of directional data is given. The data image for linear variables is reviewed, then extended to directional variables by displaying direction using a color scale composed of a sequence of four or more color gradients with continuity between sequences and ordered intuitively in a color wheel such that the color of the 0deg angle is the same as the color of the 360deg angle. Cross over, which arose in automating the summarization of historical wind data, and color discontinuity resulting from the use a single color gradient in computational fluid dynamics visualization are eliminated. The new method provides for simultaneous resolution of detail on a small scale and overall structure on a large scale. Example circular data images are given of a global view of average wind direction of El Nino periods, computed rocket motor internal combustion flow, a global view of direction of the horizontal component of earth's main magnetic field on 9/15/2004, and Space Shuttle solid rocket motor nozzle vectoring.